CN106527384A - Production control mechanism based on cloud platform assisted switching strategy - Google Patents
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Abstract
本发明公开了一种基于云平台辅助切换策略的生产调控机制，步骤包括：云平台获取客户端的订单信息，采用实时分析处理技术处理订单信息和柔性生产系统中生产设备的状态信息；柔性生产系统根据反馈机制，采用多种类型的传感器来检测生产设备的运行状态信息，并将检测结果通过云平台提供的数据通道接口上传至云平台的数据处理中心；云平台采用离线分析处理技术，对经过处理后的订单信息结合生产设备运行状态信息的检测结果进行整合；云平台决策出柔性生产系统的运行控制策略；云平台对智能设备下达决策指令；智能设备进行功能模块化，然后提供相应的命令参数接口用于接收云平台的决策指令。本发明具有更好的分辨率重构效果、更快速的重构速率。
The invention discloses a production control mechanism based on a cloud platform-assisted switching strategy. The steps include: the cloud platform obtains the order information of the client, and uses real-time analysis and processing technology to process the order information and the status information of the production equipment in the flexible production system; the flexible production system According to the feedback mechanism, various types of sensors are used to detect the operation status information of the production equipment, and the detection results are uploaded to the data processing center of the cloud platform through the data channel interface provided by the cloud platform; The processed order information is integrated with the detection results of the operating status information of the production equipment; the cloud platform decides the operation control strategy of the flexible production system; the cloud platform issues decision-making instructions to the smart devices; the smart devices perform functional modularization, and then provide corresponding commands The parameter interface is used to receive decision-making instructions from the cloud platform. The invention has better resolution reconstruction effect and faster reconstruction rate.
Description
技术领域technical field
本发明涉及工业柔性生产系统的信息处理技术领域，尤其涉及一种基于云平台辅助切换策略的生产调控机制。The invention relates to the technical field of information processing of industrial flexible production systems, in particular to a production control mechanism based on a cloud platform-assisted switching strategy.
背景技术Background technique
随着人们对商品需求越来越多样化与个性化，传统的制造体系将发生剧烈的改变，由单一的、大批量的固定式生产模式向小规模、多批量、多类型的灵活生产模式转变，以此来动态响应用户特性化需求。近年来，随着云计算、大数据、工业4.0的模型及概念的提出，世界制造产业开始向智能制造方向发展，将制造技术、网络技术及数据处理技术等集成应用于“设计----生产----管理”，在生产过程中进行感知、分析、决策及控制，从而实现对客户需求的动态响应。As people's demand for commodities becomes more and more diversified and personalized, the traditional manufacturing system will undergo drastic changes, from a single, large-volume fixed production model to a small-scale, multi-batch, and multi-type flexible production model , in order to dynamically respond to the user's personalized needs. In recent years, with the introduction of cloud computing, big data, and industry 4.0 models and concepts, the world's manufacturing industry has begun to develop towards intelligent manufacturing, integrating manufacturing technology, network technology, and data processing technology into "design---- Production----management", perception, analysis, decision-making and control in the production process, so as to realize the dynamic response to customer needs.
在工业生产过程中，每天都会产生大量的数据信息，这些数据看似体积庞大而无用，因此在工业控制领域中几乎不被看中而随之被忽略。然而这些大数据是整个工业系统的运行产物，能实际的反映出系统在某一时刻的状态，甚至可以通过分析这些大数据来控制系统的运行周期等，因此，可以通过上述方式为整个工业系统进行相关的产能优化配置。In the process of industrial production, a large amount of data information is generated every day. These data seem to be huge and useless, so they are almost ignored in the field of industrial control. However, these big data are the products of the operation of the entire industrial system, which can actually reflect the state of the system at a certain moment, and even control the operating cycle of the system by analyzing these big data. Perform relevant capacity optimization configurations.
当前的工业体系已经实现了部分智能化与自动化，然而这些离散的控制单元未能形成一套可相互协调、高度融合的统一智能制造系统整体，每个控制单元之间仍需大量相关技术人员的参与才能维持正常运行。在这一系列的生产调配过程中，会因为机器设备生产模式固化、运行故障或人为失误等原因，不利于工业资源的优化配置，并且会在工业生产中造成巨大损失。然而，云计算是一种基于互联网的计算方式，通过这种方式，共享的软硬件资源和信息可以按需提供给特定设备，通过提供一套通用的网络业务应用的服务体系，可以让工业物联网中以兆计算的各类物品的实时动态分析变得可能。因此，本发明提出的一种基于云平台辅助切换策略的生产调控机制，将为今后工业的智能化与自动化发展以及提高生产效率和生产可靠性起到一定的推动作用。The current industrial system has achieved partial intelligence and automation. However, these discrete control units have not been able to form a unified intelligent manufacturing system that can be coordinated and highly integrated. Each control unit still requires a large number of relevant technical personnel. Participation is necessary to maintain normal operation. In this series of production allocation process, due to reasons such as solidification of machine equipment production mode, operation failure or human error, it is not conducive to the optimal allocation of industrial resources, and will cause huge losses in industrial production. However, cloud computing is a computing method based on the Internet. In this way, shared hardware and software resources and information can be provided to specific devices on demand. By providing a general service system for network business applications, industrial objects can be Real-time dynamic analysis of various items in the network becomes possible. Therefore, a production control mechanism based on a cloud platform-assisted switching strategy proposed by the present invention will play a certain role in promoting the intelligent and automatic development of industries and the improvement of production efficiency and production reliability in the future.
发明内容Contents of the invention
本发明要解决的技术问题在于，提供一种基于云平台辅助切换策略的生产调控机制，具有更好的分辨率重构效果、更快速的重构速率。The technical problem to be solved by the present invention is to provide a production control mechanism based on a cloud platform-assisted switching strategy, which has a better resolution reconstruction effect and a faster reconstruction rate.
为解决上述技术问题，本发明提供如下技术方案：一种基于云平台辅助切换策略的生产调控机制，包括以下步骤：In order to solve the above-mentioned technical problems, the present invention provides the following technical solutions: a production control mechanism based on a cloud platform-assisted switching strategy, comprising the following steps:
S1、云平台采用实时分析处理技术，处理客户端的订单信息和柔性生产系统中生产设备的状态信息；S1. The cloud platform uses real-time analysis and processing technology to process the order information of the client and the status information of the production equipment in the flexible production system;
S2、柔性生产系统的反馈机制采用多种类型的传感器来检测生产设备的运行状态信息，并将检测结果通过云平台提供的数据通道接口上传至云平台的数据处理中心；S2. The feedback mechanism of the flexible production system uses various types of sensors to detect the operating status information of the production equipment, and uploads the detection results to the data processing center of the cloud platform through the data channel interface provided by the cloud platform;
S3、云平台采用离线分析处理技术，对经过实时分析处理后的订单信息结合生产设备的状态信息分析结果进行整合；根据整合结果，云平台决策出柔性生产系统的运行控制策略；根据运行控制策略，云平台对智能设备下达决策指令；S3. The cloud platform adopts offline analysis and processing technology to integrate the order information after real-time analysis and processing combined with the analysis results of the status information of the production equipment; according to the integration results, the cloud platform decides the operation control strategy of the flexible production system; according to the operation control strategy , the cloud platform issues decision-making instructions to smart devices;
S4、智能设备进行功能模块化，然后提供相应的命令参数接口用于接收云平台的决策指令。S4. The smart device performs functional modularization, and then provides a corresponding command parameter interface for receiving decision-making instructions from the cloud platform.
进一步地，所述步骤S1中，云平台获取客户端的订单信息后，采用流式计算方式将网络用户在线下达的多种类型的并发的订单进行初步数据信息的实时分类、归类与统计。Further, in the step S1, after the cloud platform acquires the order information of the client, it uses stream computing to perform real-time classification, classification and statistics of preliminary data information on various types of concurrent orders placed online by network users.
进一步地，所述步骤S1中实时分析处理技术处理订单信息和柔性生产系统中生产设备的状态信息，具体为：对来自客户端的订单信息，云平台进行编号和加盖时间戳；对来自柔性生产系统中的所有生产设备的运行、停机、故障状态信息进行辨识和分解，用以实现整个柔性生产系统的实时运作监控。Further, the real-time analysis and processing technology in step S1 processes the order information and the status information of the production equipment in the flexible production system, specifically: numbering and stamping the order information from the client on the cloud platform; The operation, shutdown, and fault status information of all production equipment in the system are identified and decomposed to realize real-time operation monitoring of the entire flexible production system.
进一步地，所述步骤S2的柔性生产系统包括多个智能加工单元，所述多种类型的传感器包括光电传感器、温度传感器和RFID读写器；所述智能加工单元设置相应的传感器；通过相应的传感器检测柔性生产系统中加工工件所完成的工序样式和剩余工序量，以及检测柔性生产系统的执行机构的运行状态；所述智能加工单元使用自身的信号转换模块将传感器检测信息处理后发送至云平台。Further, the flexible production system in step S2 includes a plurality of intelligent processing units, and the various types of sensors include photoelectric sensors, temperature sensors and RFID readers; the intelligent processing units are provided with corresponding sensors; through corresponding The sensor detects the completed process style and remaining process amount of the workpiece in the flexible production system, and detects the operating status of the actuator of the flexible production system; the intelligent processing unit uses its own signal conversion module to process the sensor detection information and send it to the cloud platform.
进一步地，所述信号转换模块通过无线方式与云平台进行网络连接，并采用HTTP协议进行数据传输；所述信号转换模块将传感器检测信息进行数据归类和格式调整后发送至云平台相应的数据通道接口，进而发送至云平台的数据处理中心进行数据的分析处理。Further, the signal conversion module is connected to the cloud platform through a wireless network, and uses the HTTP protocol for data transmission; the signal conversion module sends the sensor detection information to the cloud platform after data classification and format adjustment. channel interface, and then sent to the data processing center of the cloud platform for data analysis and processing.
进一步地，所述步骤S3中，在离线分析处理技术过程中，云平台将经过流式计算方式处理后的订单按类型进行再次归类，并计算出所需的零件样式和零件数量，结合生产设备的运行状态情况和可运行的数量进行分析，若在一个生产周期内且订单的任务量耗时不超过生产周期时，则优先按照订单所属类别数量较大的进行生产；若在一个生产周期内且某一类型的订单任务量耗时超过生产周期时，则此类型订单优先生产，其它订单将结合此类型订单的余下部分依次规划到下一个生产周期的生产任务中。Further, in the step S3, in the process of offline analysis and processing technology, the cloud platform classifies the orders processed by stream computing by type again, and calculates the required part style and part quantity, and combines the production Analyze the operating status of the equipment and the quantity that can be operated. If it is within a production cycle and the task time of the order does not exceed the production cycle, it will be given priority to produce according to the category that the order belongs to; if it is within a production cycle If the amount of tasks for a certain type of order exceeds the production cycle, this type of order will be produced first, and other orders will be planned in turn in the production tasks of the next production cycle in combination with the rest of this type of order.
进一步地，所述步骤S3中运行控制策略，具体为：根据柔性生产系统反馈回来的设备状态信息而适时调整生产周期，并结合订单任务重组生产模式；利用运行控制策略，柔性生产系统在不需要人员操作的情况下，对自身进行生产模式的调整，用于实现小规模、多批量、多类型的生产任务自动切换功能。Further, the operation control strategy in the step S3 is specifically: timely adjust the production cycle according to the equipment status information fed back by the flexible production system, and reorganize the production mode in combination with the order task; use the operation control strategy, the flexible production system does not need In the case of personnel operation, it adjusts its own production mode to realize the automatic switching function of small-scale, multi-batch and multi-type production tasks.
进一步地，所述步骤S4，具体为：在柔性生产系统中，将具有加工某一部分零件或拥有某一部分生产职能的生产加工子系统独立出来；所述独立出来的生产加工子系统作为一个相对独立的智能生产单元，并将其各个机械结构的执行动作进行功能模块化封装，以此便于云平台决策指令的简化、减小数据传输量以及所述智能生产单元中的各个机器设备接受并执行相应的命令。Further, the step S4 is specifically: in the flexible production system, separate the production and processing subsystem that processes a certain part or has a certain production function; the independent production and processing subsystem is used as a relatively independent intelligent production unit, and perform functional modular packaging of the execution actions of each mechanical structure, so as to facilitate the simplification of cloud platform decision-making instructions, reduce the amount of data transmission, and each machine equipment in the intelligent production unit accepts and executes corresponding The command.
进一步地，所述多种类型的传感器对所述智能生产单元进行检测，将所述智能加工单元的运行、停机和故障的状态信息以及在所述智能加工单元处的产品的加工工位信息，通过信号转换模块和云平台提供的数据传送接口传入数据处理中心。Further, the various types of sensors detect the intelligent production unit, and the status information of the operation, shutdown and failure of the intelligent processing unit and the processing station information of the product at the intelligent processing unit, It is transmitted to the data processing center through the signal conversion module and the data transmission interface provided by the cloud platform.
采用上述技术方案后，本发明至少具有如下有益效果：After adopting the above technical solution, the present invention has at least the following beneficial effects:
(1)、本发明采用了流式计算模式与离线计算模式，流式计算实现实时处理客户订单业务，时间段一般设置在人们日常生活购买行为活跃的时间段(如白天)，而离线计算实现业务最终决策处理，一般设置在人们日常作息的休息时间段(如夜晚)；通过这两种方式结合，分时高效的利用云平台的计算资源，可以节约计算处理成本，又能为生产制造系统提供合适的决策机制；(1), the present invention adopts the streaming computing mode and the offline computing mode, and the streaming computing realizes real-time processing of customer order business. The final decision-making process of the business is generally set during the rest time period of people's daily work and rest (such as at night); through the combination of these two methods, the computing resources of the cloud platform can be efficiently used in time-sharing, which can save computing and processing costs, and can also be used for manufacturing systems. provide appropriate decision-making mechanisms;
(2)、本发明在柔性生产系统中实现生产线业务变更要求时，通过使用云平台辅助切换策略的生产机制，省略了繁琐人工调节机器设备生产模式参数环节，同时能够排除故障自适应调节生产模式，并能进行生产模式无缝切换，这将减轻生产成本、减少人为操作失误、节约时间、提高生产效率，并将进一步实现工业生产系统的智能化、无人化与自动化生产。(2) When the present invention implements the business change requirements of the production line in the flexible production system, by using the production mechanism of the cloud platform to assist the switching strategy, the cumbersome manual adjustment of the parameters of the production mode of the machine and equipment is omitted, and at the same time, it can eliminate faults and self-adapt the adjustment of the production mode , and can seamlessly switch production modes, which will reduce production costs, reduce human error, save time, improve production efficiency, and further realize the intelligent, unmanned and automated production of industrial production systems.
附图说明Description of drawings
图1是本发明实施例的总体流程结构示意图；Fig. 1 is a schematic diagram of the overall process structure of an embodiment of the present invention;
图2是本发明一种基于云平台辅助切换策略的生产调控机制的智能生产单元执行动作模块化封装示意图；Fig. 2 is a schematic diagram of an intelligent production unit execution action modularization encapsulation based on a production control mechanism based on a cloud platform auxiliary switching strategy in the present invention;
图3是本发明一种基于云平台辅助切换策略的生产调控机制的流式计算模式处理客户订单信息流程示意图；Fig. 3 is a schematic flow diagram of the stream computing mode processing customer order information of the production control mechanism based on the cloud platform auxiliary switching strategy of the present invention;
图4是本发明一种基于云平台辅助切换策略的生产调控机制的离线决策模式批量处理订单信息的流程示意图。FIG. 4 is a schematic flowchart of batch processing order information in an offline decision-making mode of a production control mechanism based on a cloud platform-assisted switching strategy in the present invention.
具体实施方式detailed description
需要说明的是，在不冲突的情况下，本申请中的实施例及实施例中的特征可以相互结合，下面结合附图和具体实施例对本申请作进一步详细说明。It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be further described in detail below in conjunction with the drawings and specific embodiments.
如附图1所示，本发明实施的总体流程结构示意图，其步骤如下：As shown in accompanying drawing 1, the overall flow chart structural representation that the present invention implements, its steps are as follows:
1)云平台通过提供订单数据处理接口，实时获取订单信息，并根据用户信息及订单提交时间为订单配置相应的ID编号和时间戳，同时以Map<Key,Value>映射方式记录其数量(如：(a1,52))；1) The cloud platform obtains order information in real time by providing an order data processing interface, and configures the corresponding ID number and timestamp for the order according to the user information and order submission time, and records its quantity in the Map<Key,Value> mapping method (such as :(a1,52));
2)云平台采用流式计算方式将众多类型与并发订制的订单进行分解、归类与统计；结合图3所示，如一组订单{(a1,n1),(b3,n2),(a1,n3),(b2,n4),(c1,n5),(b3,n6),(b2,n7),(a2,n8)}，先将其产品族类归类{A:[(a1,n1),(a1,n3),(a2,n8)],B:[(b3,n2),(b2,n4),(b3,n6),(b2,n7)],C:[(c1,n5)]}，然后进行同一族类样式数量统计{A:[(a1,n1+n3),(a2,n8)],B:[(b2,n4+n7),(b3,n2+n6)],C:[(c1,n5)]}，最后将其初步处理结果送入云平台的数据存储中心；2) The cloud platform uses streaming computing to decompose, classify and count many types and concurrently ordered orders; as shown in Figure 3, such as a group of orders {(a1,n1),(b3,n2),(a1 ,n3),(b2,n4),(c1,n5),(b3,n6),(b2,n7),(a2,n8)}, first classify its product family {A:[(a1, n1),(a1,n3),(a2,n8)],B:[(b3,n2),(b2,n4),(b3,n6),(b2,n7)],C:[(c1, n5)]}, and then count the number of styles of the same family {A:[(a1,n1+n3),(a2,n8)],B:[(b2,n4+n7),(b3,n2+n6) ], C:[(c1,n5)]}, and finally send the preliminary processing results to the data storage center of the cloud platform;
3)在一个生产周期内，云平台的数据处理中心汇集了流式计算方式对客户订单的初步处理结果，在下一周期开始前，云平台将其结合生产系统反馈的信息进行离线决策计算。3) During a production cycle, the data processing center of the cloud platform collects the preliminary processing results of customer orders by stream computing. Before the start of the next cycle, the cloud platform combines it with the information fed back by the production system for offline decision-making calculations.
如图4所示，在进行离线决策过程中，云平台将订单信息进行进一步的归类统计，离线归类统计的过程与流式计算归类统计的过程类似，计算出符合下一个生产周期的任务量，同时根据任务量适当调节生产周期T(其中：1≤T≤24，默认值T0＝24)长短。在这一过程中将会出现两种情况：第一种情况是计算的结果Re1小于等于该生产周期任务量的阀值F(τ)，则下一生产周期将直接完成订单任务；第二种情况是计算的结果Re1大于该生产周期任务量的阀值F(τ)，且是其N(N∈R,且(1<N<3))倍时，将优先完成该订单，并依次向下一个生产周期递交该订单任务的剩余部分Re2。As shown in Figure 4, during the offline decision-making process, the cloud platform further classifies and counts the order information. The process of offline classification and statistics is similar to the process of streaming computing classification and statistics, and calculates the order information that meets the next production cycle The amount of tasks, and at the same time appropriately adjust the length of the production cycle T (where: 1≤T≤24, the default value T 0 =24) according to the amount of tasks. In this process, there will be two situations: the first situation is that the calculated result Re1 is less than or equal to the threshold value F(τ) of the task amount of the production cycle, and the order task will be completed directly in the next production cycle; the second situation The situation is that when the calculated result Re 1 is greater than the threshold value F(τ) of the task quantity of the production cycle, and is N(N∈R, and (1<N<3)) times, the order will be completed first, and in turn Submit the remaining part Re 2 of the order task to the next production cycle.
4)生产系统中将具有相对独立加工某一部分工序的机器设备和执行机构，结合相应的传感设备和信号转换模块组成一个智能加工单元。通过传感器检测整个智能加工单元的加工制造过程状态，将智能加工单元的运行、停止、故障等状态信息以及在该智能加工单元处的产品的加工工位信息，通过信号转换模块和云平台提供的数据传送接口传入数据处理中心。4) In the production system, the machine equipment and actuators that process a certain part of the process independently will be combined with the corresponding sensing equipment and signal conversion modules to form an intelligent processing unit. Detect the processing and manufacturing process status of the entire intelligent processing unit through sensors, and provide the status information of the intelligent processing unit, such as operation, stop, and fault, and the processing station information of the product at the intelligent processing unit, through the signal conversion module and the cloud platform. The data transmission interface is transmitted to the data processing center.
云平台将生产系统反馈上来的状态信息进行分析处理。假设生产系统中的智能加工单元共有M个，第i(其中i∈[1,M])个智能加工单元的可能的状态输出为集合Per(i)＝{Run(i),Stop(i),Fault(i)}的一种。若生产系统采用冗余生产加工方式，即每个智能加工单元可以实现多种加工工序或每一种工序都可由多个智能加工单元进行加工，设每样工序的冗余度Share(j)(其中j为某种订单的第j种工序)的最大值为3。The cloud platform analyzes and processes the status information fed back from the production system. Assuming that there are M intelligent processing units in the production system, the possible state output of the i-th (where i∈[1,M]) intelligent processing unit is the set Per(i)={Run(i),Stop(i) , a type of Fault(i)}. If the production system adopts a redundant production and processing method, that is, each intelligent processing unit can realize multiple processing procedures or each procedure can be processed by multiple intelligent processing units, the redundancy of each procedure Share(j)( Where j is the jth process of a certain order) the maximum value is 3.
若在一个生产周期内的订单任务中，由于某一族类的产品在生产过程中第i个智能加工单元在生产过程中加工第j种工序中发生故障，此时，该智能生产单元的信号转换模块向云平台发送Fault(i)信号，云平台将其对应工序冗余度Share(j)的值变为2，此时将生产周期T相应的延长，并停止第i个智能加工单元的生产任务，转而将需要完成第j种工序的半成品向其它冗余智能生产单元调度。当该工序的冗余度Share(j)＝0时，云平台将停止该族类类型的产品生产，同时云平台将决策出该生产周期内的订单任务中其它无需此工序的族类产品的加工指令。当第j种工序对应的故障智能生产单元修复之后，该智能生产单元的状态输出为Stop(i)，此时云平台检测该工序是否属于正在加工族类产品的工序，若是，则将其归并到生产线上，其状态输出转为Run(i)，Share(j)＝Share(j)+1，并将生产周期T的时间缩短；若否，则让其继续保持状态输出为Stop(i)，并且其它相关参数保持不变，并等待云平台下一个执行决策的制定。If in an order task within a production cycle, due to a failure of the ith intelligent processing unit in the production process of the jth process in the production process of a certain type of product, at this time, the signal conversion of the intelligent production unit The module sends a Fault(i) signal to the cloud platform, and the cloud platform changes the value of the corresponding process redundancy Share(j) to 2, at this time, the production cycle T is correspondingly extended, and the production of the i-th intelligent processing unit is stopped In turn, the semi-finished products that need to complete the jth process are dispatched to other redundant intelligent production units. When the redundancy of this process Share(j)=0, the cloud platform will stop the production of this type of product, and at the same time, the cloud platform will determine the number of other family products that do not need this process in the order task in the production cycle. Processing instructions. When the faulty intelligent production unit corresponding to the jth process is repaired, the state output of the intelligent production unit is Stop(i), and the cloud platform detects whether the process belongs to the process of processing the family product, and if so, merges it On the production line, its state output is changed to Run(i), Share(j)=Share(j)+1, and the time of production cycle T is shortened; if not, then let it continue to maintain the state output as Stop(i) , and other relevant parameters remain unchanged, and wait for the cloud platform to make the next execution decision.
5)生产系统机组工作模式的制定，需要云平台整合订单的分析结果和机组状态的分析结果。在同一个订单任务中，按所属族类产品数量多的优先生产，每个族类的产品按其加工特征对应一套工作模式，每套工作模式中都兼容了生产设备运行、停机和故障状态的诊断与切换功能。5) The formulation of the working mode of the unit in the production system requires the cloud platform to integrate the analysis results of the order and the status of the unit. In the same order task, the product with the largest number of products in the family is given priority in production, and each family of products corresponds to a set of working modes according to their processing characteristics, and each working mode is compatible with the operation, shutdown and failure status of production equipment Diagnosis and switching functions.
6)云平台决策命令下达到生产系统机组设备，由于生产系统中的每个智能生产单元的执行动作控制方法已进行了相关的模块化封装，因此，云平台的决策命令可以以一组参数形式的指令进行传递和对机组设备的控制。6) The decision-making command of the cloud platform is sent to the unit equipment of the production system. Since the execution action control method of each intelligent production unit in the production system has been packaged in related modules, the decision-making command of the cloud platform can be in the form of a set of parameters The command is transmitted and the control of the unit equipment is carried out.
如图2所示，每个生产单元将自身的执行动作进行功能模块化封装，并提供执行这些功能的命令参数的应用程序接口，通过相应的信号转换模块接收并解析来至云平台的工作指令；云平台的指令库储存有各个族类产品加工的指令，可以通过订单任务找出产品加工所对应的指令。在指令的数据包中，包含有该产品加工时每一道工序对应的智能生产单元的机组编号、启停动作及相应的操作参数。通过这种方式，可以实现云平台对整个生产系统的工作模式的控制。As shown in Figure 2, each production unit performs modular packaging of its own execution actions, and provides an application program interface for command parameters to perform these functions, and receives and parses work instructions from the cloud platform through the corresponding signal conversion module ; The instruction library of the cloud platform stores instructions for processing various types of products, and the instructions corresponding to product processing can be found through order tasks. In the data packet of the instruction, it contains the unit number, start-stop action and corresponding operating parameters of the intelligent production unit corresponding to each process during the product processing. In this way, the cloud platform can control the working mode of the entire production system.
根据上述的云平台对生产系统决策控制的工作模式，使之形成一个可动态响应客户个性化需求的闭环智能化的柔性制造系统，从而摆脱了人的控制参与，节约了工作时间和生产资源，提高了工厂的生产效率和企业在市场供求关系的应变性。According to the above-mentioned working mode of the cloud platform for decision-making control of the production system, it forms a closed-loop intelligent flexible manufacturing system that can dynamically respond to the individual needs of customers, thus getting rid of human control and participation, saving working time and production resources. Improve the production efficiency of the factory and the adaptability of the enterprise in the relationship between supply and demand in the market.
尽管已经示出和描述了本发明的实施例，对于本领域的普通技术人员而言，可以理解的是，在不脱离本发明的原理和精神的情况下可以对这些实施例进行多种等效的变化、修改、替换和变型，本发明的范围由所附权利要求及其等同范围限定。While embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various equivalents can be made to these embodiments without departing from the principles and spirit of the invention. Changes, modifications, substitutions and variations, the scope of the present invention is defined by the appended claims and their equivalents.
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